The aim of our research is to complement structural studies (X-rays,
NMR, Electron microscopy) with in silico studies, to:

better
determine and predict three-dimensional
structures;

better
understand molecular
recognition and molecular
interactions.

Our
research topics include medically relevant molecular
processes (infectious
diseases,
cancer, and the action of general anesthetics). Collaboration with experimental groups on
campus, and our own experimental projects, are of
fundamental importance for the group.

We develop
strategies for the structural analysis of NMR data to
make experimental structure
determination more
reliable, and allow, for the first time, to obtain an
unbiased estimate of quality of an NMR structure. We
apply similar methods for structure prediction. We mostly use our homology modeling
“pipeline” to answer questions about protein
function. Other developments include new probabilistic
methods for sequence alignment RNA structure prediction,
and gene
prediction by physics based
genome analysis.

We study
the dynamics of protein-protein interactions
by docking and molecular dynamics
calculations. This provides us new insights into the
interplay between protein flexibility and molecular
recognition, and the thermodynamics of protein-ligand
interactions. The prediction of conformational changes
during the binding of two proteins, or a protein and a
small ligand, remains an important aim. Using a novel
molecular dynamics method, we have obtained very
encouraging results recently for the protein HasA binding
to heme.

The field
of protein-ligand
interactions has
fundamental as well as more applied aspects. In several
collaborations with experimental groups we use empirical
strategies for ligand docking and virtual screening. Targets include proteins from
P. falciparum, T. brucei, T. cruzi,
M. tuberculosis. We have
identified several inhibitors for proteins from
P. falciparum, M.
tuberculosis that could be
validated experimentally.

Illustration of an important part of the activity of the unit. Starting from structural information for a protein, we use various methods to predict and characterize its interactions with other molecules. The results serve as input for further experimental studies.